Module aws_lambda_powertools.utilities.parser
Advanced event_parser utility
Expand source code
"""Advanced event_parser utility
"""
from . import envelopes
from .envelopes import BaseEnvelope
from .parser import event_parser, parse
from .pydantic import BaseModel, Field, ValidationError, root_validator, validator
__all__ = [
"event_parser",
"parse",
"envelopes",
"BaseEnvelope",
"BaseModel",
"Field",
"validator",
"root_validator",
"ValidationError",
]
Sub-modules
aws_lambda_powertools.utilities.parser.envelopes
aws_lambda_powertools.utilities.parser.exceptions
aws_lambda_powertools.utilities.parser.models
aws_lambda_powertools.utilities.parser.parser
aws_lambda_powertools.utilities.parser.pydantic
aws_lambda_powertools.utilities.parser.types
-
Generics and other shared types used across parser
Functions
def Field(default: Any = PydanticUndefined, *, default_factory: Union[Callable[[], Any], NoneType] = None, alias: unicode = None, title: unicode = None, description: unicode = None, const: bool = None, gt: float = None, ge: float = None, lt: float = None, le: float = None, multiple_of: float = None, min_items: int = None, max_items: int = None, min_length: int = None, max_length: int = None, allow_mutation: bool = True, regex: unicode = None, **extra: Any) ‑> Any
-
Used to provide extra information about a field, either for the model schema or complex validation. Some arguments apply only to number fields (
int
,float
,Decimal
) and some apply only tostr
.:param default: since this is replacing the field’s default, its first argument is used to set the default, use ellipsis (
…
) to indicate the field is required :param default_factory: callable that will be called when a default value is needed for this field If bothdefault
anddefault_factory
are set, an error is raised. :param alias: the public name of the field :param title: can be any string, used in the schema :param description: can be any string, used in the schema :param const: this field is required and must take it's default value :param gt: only applies to numbers, requires the field to be "greater than". The schema will have anexclusiveMinimum
validation keyword :param ge: only applies to numbers, requires the field to be "greater than or equal to". The schema will have aminimum
validation keyword :param lt: only applies to numbers, requires the field to be "less than". The schema will have anexclusiveMaximum
validation keyword :param le: only applies to numbers, requires the field to be "less than or equal to". The schema will have amaximum
validation keyword :param multiple_of: only applies to numbers, requires the field to be "a multiple of". The schema will have amultipleOf
validation keyword :param min_length: only applies to strings, requires the field to have a minimum length. The schema will have amaximum
validation keyword :param max_length: only applies to strings, requires the field to have a maximum length. The schema will have amaxLength
validation keyword :param allow_mutation: a boolean which defaults to True. When False, the field raises a TypeError if the field is assigned on an instance. The BaseModel Config must set validate_assignment to True :param regex: only applies to strings, requires the field match agains a regular expression pattern string. The schema will have apattern
validation keyword :param **extra: any additional keyword arguments will be added as is to the schema def event_parser(handler: Callable[[Any, aws_lambda_powertools.utilities.lambda_context.LambdaContext], Any], event: Dict[str, Any], context: LambdaContext, model: ~Model, envelope: Union[~Envelope, NoneType] = None) ‑> Any
-
Lambda handler decorator to parse & validate events using Pydantic models
It requires a model that implements Pydantic BaseModel to parse & validate the event.
When an envelope is given, it'll use the following logic:
- Parse the event against the envelope model first e.g. EnvelopeModel(**event)
- Envelope will extract a given key to be parsed against the model e.g. event.detail
This is useful when you need to confirm event wrapper structure, and b) selectively extract a portion of your payload for parsing & validation.
NOTE: If envelope is omitted, the complete event is parsed to match the model parameter BaseModel definition.
Example
Lambda handler decorator to parse & validate event
class Order(BaseModel): id: int description: str ... @event_parser(model=Order) def handler(event: Order, context: LambdaContext): ...
Lambda handler decorator to parse & validate event - using built-in envelope
class Order(BaseModel): id: int description: str ... @event_parser(model=Order, envelope=envelopes.EVENTBRIDGE) def handler(event: Order, context: LambdaContext): ...
Parameters
handler
:Callable
- Method to annotate on
event
:Dict
- Lambda event to be parsed & validated
context
:LambdaContext
- Lambda context object
model
:Model
- Your data model that will replace the event.
envelope
:Envelope
- Optional envelope to extract the model from
Raises
ValidationError
- When input event does not conform with model provided
InvalidModelTypeError
- When model given does not implement BaseModel
InvalidEnvelopeError
- When envelope given does not implement BaseEnvelope
Expand source code
@lambda_handler_decorator def event_parser( handler: Callable[[Any, LambdaContext], Any], event: Dict[str, Any], context: LambdaContext, model: Model, envelope: Optional[Envelope] = None, ) -> Any: """Lambda handler decorator to parse & validate events using Pydantic models It requires a model that implements Pydantic BaseModel to parse & validate the event. When an envelope is given, it'll use the following logic: 1. Parse the event against the envelope model first e.g. EnvelopeModel(**event) 2. Envelope will extract a given key to be parsed against the model e.g. event.detail This is useful when you need to confirm event wrapper structure, and b) selectively extract a portion of your payload for parsing & validation. NOTE: If envelope is omitted, the complete event is parsed to match the model parameter BaseModel definition. Example ------- **Lambda handler decorator to parse & validate event** class Order(BaseModel): id: int description: str ... @event_parser(model=Order) def handler(event: Order, context: LambdaContext): ... **Lambda handler decorator to parse & validate event - using built-in envelope** class Order(BaseModel): id: int description: str ... @event_parser(model=Order, envelope=envelopes.EVENTBRIDGE) def handler(event: Order, context: LambdaContext): ... Parameters ---------- handler: Callable Method to annotate on event: Dict Lambda event to be parsed & validated context: LambdaContext Lambda context object model: Model Your data model that will replace the event. envelope: Envelope Optional envelope to extract the model from Raises ------ ValidationError When input event does not conform with model provided InvalidModelTypeError When model given does not implement BaseModel InvalidEnvelopeError When envelope given does not implement BaseEnvelope """ parsed_event = parse(event=event, model=model, envelope=envelope) logger.debug(f"Calling handler {handler.__name__}") return handler(parsed_event, context)
def parse(event: Dict[str, Any], model: ~Model, envelope: Union[~Envelope, NoneType] = None) ‑> ~Model
-
Standalone function to parse & validate events using Pydantic models
Typically used when you need fine-grained control over error handling compared to event_parser decorator.
Example
Lambda handler decorator to parse & validate event
from aws_lambda_powertools.utilities.parser import ValidationError class Order(BaseModel): id: int description: str ... def handler(event: Order, context: LambdaContext): try: parse(model=Order) except ValidationError: ...
Lambda handler decorator to parse & validate event - using built-in envelope
class Order(BaseModel): id: int description: str ... def handler(event: Order, context: LambdaContext): try: parse(model=Order, envelope=envelopes.EVENTBRIDGE) except ValidationError: ...
Parameters
event
:Dict
- Lambda event to be parsed & validated
model
:Model
- Your data model that will replace the event
envelope
:Envelope
- Optional envelope to extract the model from
Raises
ValidationError
- When input event does not conform with model provided
InvalidModelTypeError
- When model given does not implement BaseModel
InvalidEnvelopeError
- When envelope given does not implement BaseEnvelope
Expand source code
def parse(event: Dict[str, Any], model: Model, envelope: Optional[Envelope] = None) -> Model: """Standalone function to parse & validate events using Pydantic models Typically used when you need fine-grained control over error handling compared to event_parser decorator. Example ------- **Lambda handler decorator to parse & validate event** from aws_lambda_powertools.utilities.parser import ValidationError class Order(BaseModel): id: int description: str ... def handler(event: Order, context: LambdaContext): try: parse(model=Order) except ValidationError: ... **Lambda handler decorator to parse & validate event - using built-in envelope** class Order(BaseModel): id: int description: str ... def handler(event: Order, context: LambdaContext): try: parse(model=Order, envelope=envelopes.EVENTBRIDGE) except ValidationError: ... Parameters ---------- event: Dict Lambda event to be parsed & validated model: Model Your data model that will replace the event envelope: Envelope Optional envelope to extract the model from Raises ------ ValidationError When input event does not conform with model provided InvalidModelTypeError When model given does not implement BaseModel InvalidEnvelopeError When envelope given does not implement BaseEnvelope """ if envelope and callable(envelope): try: logger.debug(f"Parsing and validating event model with envelope={envelope}") return envelope().parse(data=event, model=model) except AttributeError: raise InvalidEnvelopeError(f"Envelope must implement BaseEnvelope, envelope={envelope}") try: logger.debug("Parsing and validating event model; no envelope used") if isinstance(event, str): return model.parse_raw(event) return model.parse_obj(event) except AttributeError: raise InvalidModelTypeError(f"Input model must implement BaseModel, model={model}")
def root_validator(*, pre: bool = False, allow_reuse: bool = False, skip_on_failure: bool = False) ‑> Union[classmethod, Callable[[Callable[..., Any]], classmethod]]
-
Decorate methods on a model indicating that they should be used to validate (and perhaps modify) data either before or after standard model parsing/validation is performed.
def validator(*fields: unicode, pre: bool = False, each_item: bool = False, always: bool = False, check_fields: bool = True, whole: bool = None, allow_reuse: bool = False) ‑> Callable[[Callable[..., Any]], classmethod]
-
Decorate methods on the class indicating that they should be used to validate fields :param fields: which field(s) the method should be called on :param pre: whether or not this validator should be called before the standard validators (else after) :param each_item: for complex objects (sets, lists etc.) whether to validate individual elements rather than the whole object :param always: whether this method and other validators should be called even if the value is missing :param check_fields: whether to check that the fields actually exist on the model :param allow_reuse: whether to track and raise an error if another validator refers to the decorated function
Classes
class BaseEnvelope
-
ABC implementation for creating a supported Envelope
Expand source code
class BaseEnvelope(ABC): """ABC implementation for creating a supported Envelope""" @staticmethod def _parse(data: Optional[Union[Dict[str, Any], Any]], model: Type[Model]) -> Union[Model, None]: """Parses envelope data against model provided Parameters ---------- data : Dict Data to be parsed and validated model : Type[Model] Data model to parse and validate data against Returns ------- Any Parsed data """ if data is None: logger.debug("Skipping parsing as event is None") return data logger.debug("parsing event against model") if isinstance(data, str): logger.debug("parsing event as string") return model.parse_raw(data) return model.parse_obj(data) @abstractmethod def parse(self, data: Optional[Union[Dict[str, Any], Any]], model: Type[Model]): """Implementation to parse data against envelope model, then against the data model NOTE: Call `_parse` method to fully parse data with model provided. Example ------- **EventBridge envelope implementation example** def parse(...): # 1. parses data against envelope model parsed_envelope = EventBridgeModel(**data) # 2. parses portion of data within the envelope against model return self._parse(data=parsed_envelope.detail, model=data_model) """ return NotImplemented # pragma: no cover
Ancestors
- abc.ABC
Subclasses
- CloudWatchLogsEnvelope
- DynamoDBStreamEnvelope
- EventBridgeEnvelope
- KinesisDataStreamEnvelope
- SnsEnvelope
- SnsSqsEnvelope
- SqsEnvelope
Methods
def parse(self, data: Union[Dict[str, Any], Any, NoneType], model: Type[~Model])
-
Implementation to parse data against envelope model, then against the data model
NOTE: Call
_parse
method to fully parse data with model provided.Example
EventBridge envelope implementation example
def parse(…): # 1. parses data against envelope model parsed_envelope = EventBridgeModel(**data)
# 2. parses portion of data within the envelope against model return self._parse(data=parsed_envelope.detail, model=data_model)
Expand source code
@abstractmethod def parse(self, data: Optional[Union[Dict[str, Any], Any]], model: Type[Model]): """Implementation to parse data against envelope model, then against the data model NOTE: Call `_parse` method to fully parse data with model provided. Example ------- **EventBridge envelope implementation example** def parse(...): # 1. parses data against envelope model parsed_envelope = EventBridgeModel(**data) # 2. parses portion of data within the envelope against model return self._parse(data=parsed_envelope.detail, model=data_model) """ return NotImplemented # pragma: no cover
class BaseModel (**data: Any)
-
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
Ancestors
- pydantic.utils.Representation
Subclasses
- AlbModel
- AlbRequestContext
- AlbRequestContextData
- CloudWatchLogsData
- CloudWatchLogsDecode
- CloudWatchLogsLogEvent
- CloudWatchLogsModel
- DynamoDBStreamChangedRecordModel
- DynamoDBStreamModel
- DynamoDBStreamRecordModel
- UserIdentity
- EventBridgeModel
- KinesisDataStreamModel
- KinesisDataStreamRecord
- KinesisDataStreamRecordPayload
- S3Bucket
- S3EventRecordGlacierEventData
- S3EventRecordGlacierRestoreEventData
- S3Identity
- S3Message
- S3Model
- S3Object
- S3OwnerIdentify
- S3RecordModel
- S3RequestParameters
- S3ResponseElements
- S3ObjectConfiguration
- S3ObjectContext
- S3ObjectLambdaEvent
- S3ObjectSessionAttributes
- S3ObjectSessionContext
- S3ObjectSessionIssuer
- S3ObjectUserIdentity
- S3ObjectUserRequest
- SesMail
- SesMailCommonHeaders
- SesMailHeaders
- SesMessage
- SesModel
- SesReceipt
- SesReceiptAction
- SesReceiptVerdict
- SesRecordModel
- SnsModel
- SnsMsgAttributeModel
- SnsNotificationModel
- SnsRecordModel
- SqsAttributesModel
- SqsModel
- SqsMsgAttributeModel
- SqsRecordModel
- pydantic.env_settings.BaseSettings
Class variables
var Config
Static methods
def construct(**values: Any) ‑> Model
-
Creates a new model setting dict and fields_set from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if
Config.extra = 'allow'
was set since it adds all passed values def from_orm(obj: Any) ‑> Model
def parse_file(path: Union[str, pathlib.Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: pydantic.parse.Protocol = None, allow_pickle: bool = False) ‑> Model
def parse_obj(obj: Any) ‑> Model
def parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: pydantic.parse.Protocol = None, allow_pickle: bool = False) ‑> Model
def schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') ‑> DictStrAny
def schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) ‑> unicode
def update_forward_refs(**localns: Any) ‑> NoneType
-
Try to update ForwardRefs on fields based on this Model, globalns and localns.
def validate(value: Any) ‑> Model
Methods
def copy(self: Model, *, include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None, exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None, update: DictStrAny = None, deep: bool = False) ‑> Model
-
Duplicate a model, optionally choose which fields to include, exclude and change.
:param include: fields to include in new model :param exclude: fields to exclude from new model, as with values this takes precedence over include :param update: values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data :param deep: set to
True
to make a deep copy of the model :return: new model instance def dict(self, *, include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None, exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None, by_alias: bool = False, skip_defaults: bool = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) ‑> DictStrAny
-
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
def json(self, *, include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None, exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny')] = None, by_alias: bool = False, skip_defaults: bool = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Union[Callable[[Any], Any], NoneType] = None, **dumps_kwargs: Any) ‑> unicode
-
Generate a JSON representation of the model,
include
andexclude
arguments as perdict()
.encoder
is an optional function to supply asdefault
to json.dumps(), other arguments as perjson.dumps()
.
class ValidationError (errors: Sequence[Union[Sequence[Any], pydantic.error_wrappers.ErrorWrapper]], model: ModelOrDc)
-
Mixin to provide str, repr, and pretty methods. See #884 for more details.
pretty is used by devtools to provide human readable representations of objects.
Ancestors
- pydantic.utils.Representation
- builtins.ValueError
- builtins.Exception
- builtins.BaseException
Instance variables
var model
-
Return an attribute of instance, which is of type owner.
var raw_errors
-
Return an attribute of instance, which is of type owner.
Methods
def errors(self) ‑> List[Dict[str, Any]]
def json(self, *, indent: Union[NoneType, int, str] = 2) ‑> unicode